Deterministic Target-Barrier Coverage With Importance-Aware Sensor Deployment in IIoT

This study addresses the target-barrier coverage problem in a deterministic deployment setting, considering targets with varying levels of importance. Taking the surveillance of oil exploitation infrastructure in the Industrial Internet of Things (IIoT) as an example, different oil-related facilities within the exploitation area may have distinct levels of importance. To prevent potential damage, target-barriers must be constructed around these infrastructures. Targets of higher importance require target-barriers with extended response times, necessitating distance constraints that vary according to importance levels. To the best of our knowledge, this is the first work to address the target-barrier coverage problem while incorporating different levels of target importance. The primary objective is to minimize the number of deployed sensors needed to construct target-barriers in a deterministic manner while ensuring coverage requirements based on target importance. The minimum number of sensors required for target-barrier construction is analytically determined and formally proven. Additionally, the problem is shown to be NP-hard. Finally, simulation results are presented to evaluate the performance of the proposed algorithm.